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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

3,4‐Dicyanothiophene—a Versatile Building Block for Efficient Nonfullerene Polymer Solar Cells

Abstract In this contribution, a versatile building block, 3,4‐dicyanothiophene (DCT), which possesses structural simplicity and synthetic accessibility for constructing high‐performance, low‐cost, wide‐bandgap conjugated polymers for use as donors in polymer solar cells (PSCs), is reported. A prototype polymer, PB3TCN‐C66, and its cyano‐free analogue polymer PB3T‐C66, are synthesized to evaluate the potential of using DCT in nonfullerene PSCs. A stronger aggregation property in solution, higher thermal transition temperatures with higher enthalpies, a larger dipole moment, higher relative dielectric constant, and more linear conformation are exhibited by PB3TCN‐C66. Solar cells employing IT‐4F as the electron acceptor offer power conversion efficiencies (PCEs) of 11.2% and 2.3% for PB3TCN‐C66 and PB3T‐C66, respectively. Morphological characterizations reveal that the PB3TCN‐C66:IT‐4F blend exhibits better π–π paracrystallinity, a contracted domain size, and higher phase purity, consistent with its higher molecular interaction parameter, derived from thermodynamic calculations. Moreover, PB3TCN‐C66 offers a higher open‐circuit voltage and reduced energy loss than most state‐of‐the‐art wide‐bandgap polymers, without the need of additional electron‐withdrawing substituents. Two additional polymers derived from DCT also demonstrate promising performance with a higher PCE of 13.4% being achieved. Thus, DCT represents a versatile and promising building block for constructing high‐performance, low‐cost, conjugated polymers for application in PSCs.

Zhang, Bo↗
DOE OSTI2024

Supramolecular design principles in pseudohalides for high-performance perovskite solar mini modules

In this work, we reveal the role of non-covalent interactions, which are known to play important roles in supramolecular phenomena, in achieving efficient perovskite surface and grain boundary passivation. By using a series of pseudohalides, we find that trifluoroacetate (TFA - ) provides the strongest binding to iodide vacancies by means of non-covalent hydrogen bonding and dispersion interactions. By exploiting additional non-covalent dispersion and hydrophobic interactions in aromatic 3,3-diphenylpropylammonium (DPA + ), we present a dual-ion passivation strategy that not only minimizes the non-radiative recombination center and local chemical inhomogeneities but also induces preferentially oriented growth of α-FAPbI 3 lattice. Further, this leads to an outstanding power conversion efficiency (PCE) of 25.63% with an exceptional open-circuit voltage of 1.191 V in a perovskite solar cell with a small area, while perovskite solar mini modules with aperture areas of 25 and 64cm 2 achieved PCE of 22.47% (quasi-steady-state [QSS]-certified 20.50%) and 20.88%, respectively, with outstanding stability under high-humidity conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Optimized NiTe 2 /Ni back contacts via chemical deposition for high performance CdTe solar cells

The development of efficient and stable back contacts remains a major challenge in achieving high performance and long-term stability of CdTe thin-film solar cells. Here, this work revisits the formation of NiTe 2 by chemical bath deposition (CBD) as a back contact for CdTe devices. An optimized CBD recipe, based on high-purity precursors and the addition of copper chloride directly into the bath, was developed and applied to fabricate Cu-doped CdTe solar cells. A modified Cu-free methodology was also applied to Group V doped absorbers. The process included pinhole filling, ion milling, CBD, annealing, and sputtering to form a low-barrier back contact. Devices fabricated using this method achieved consistent open-circuit voltages (V oc ) above 800 mV and fill factors (FF) exceeding 70%. The best Cu-doped devices reached power conversion efficiencies (PCE) above 18 %, and preliminary results with Group V-doped material demonstrated compatibility of the method with high-efficiency, state-of-the-art CdTe devices. This study shows that NiTe 2 /Ni back contacts, formed via an optimized chemical process followed by sputtering of Ni, represent a promising pathway for achieving low-barrier and potentially stable back contacts in modern CdTe photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2023

Developing Efficient Benzene Additives for 19.43% Efficiency of Organic Solar Cells by Crossbreeding Effect of Fluorination and Bromination

Employing volatile solid additives have emerged as a promising method to optimize the morphology and improve the performance of organic solar cells (OSCs). However, principles governing the efficient design of solid additives remain elusive. In this work, the programmed fluorination and/or bromination on benzene core to develop efficient additives for OSCs is reported. The programmed fluorination and/or bromination endow the five halogen benzene derivatives, 1,3,5-trifluorobenzene, hexafluorobenzene, 1,3,5-tribromo-2,4,6-trifluorobenzene (TFTB), 1,3,5-tribromobenzene, and hexabromobenzene, with different melting and boiling points, volatility, as well as interactions with the host blend. Studies indicate that the additives with extremely high and low volatility are almost powerless and even detrimental to the morphology evolution. Among them, the combination of fluorine and bromine atoms on TFTB not only enables the more appropriate m.p./b.p. and volatility, but also exerts stronger molecular interactions with the host blend, giving rise to higher ordered molecular packing and more favorable morphology. Importantly, TFTB exhibits good universality to optimize the performances of OSCs with high power conversion efficiencies (PCEs; over 18%) in a group of binary blend systems, and an impressive PCE of 19.43% in the ternary PBTz-F:PM6:L8-BO system.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inorganic cesium lead mixed halide based perovskite solar materials modified with functional silver iodide

Inorganic CsPbIBr 2 perovskites have recently attracted enormous attention as a viable alternative material for optoelectronic applications due to their higher efficiency, thermal stability, suitable bandgap, and proper optical absorption. However, the CsPbIBr 2 perovskite films fabricated using a one-step deposition technique is usually comprised of small grain size with a large number of grain boundaries and compositional defects. In this work, silver iodide (AgI) will be incorporated as an additive into the CsPbIBr 2 perovskite precursor solution to prepare the unique perovskite CsI(PbBr 2 ) 1-x (AgI) x . The AgI additive in the precursor solution works as a nucleation promoter which will help the perovskite to grow and merge into a continuous film with reduced defects. With detailed characterizations, we found that incorporating AgI additive resulted in a uniform perovskite film with fewer grain boundaries, increased grain size, crystallinity, optical absorption while decreasing carrier recombination and trap density. Using the AgI in an optimum amount, we fabricated CsPbIBr 2 perovskite solar cells (PSCs) with a simple structure and achieved a power conversion efficiency (PCE) of 7.2% with a reduced hysteresis index. This work offers an alternative approach towards preparing high-quality CsPbIBr 2 perovskite films for solar cells with higher stability and other optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational evolution of high-performing unfused non-fullerene acceptors for organic solar cells

Materials optimization for organic solar cells (OSCs) is a highly active field, with many approaches using empirical experimental synthesis, computational brute force to screen a subset of chemical space, or generative machine learning methods that often require significant training sets. While these methods may find high-performing materials, they can be inefficient and time-consuming. Genetic algorithms (GAs) are an alternative approach, allowing for the “virtual synthesis” of molecules and a prediction of their “fitness” for some property, with new candidates suggested based on good characteristics of previously generated molecules. In this work, a GA is used to discover high-performing unfused non-fullerene acceptors (NFAs) based on an empirical prediction of power conversion efficiency (PCE) and provides design rules for future work. The electron-withdrawing/donating strength, as well as the sequence and symmetry, of those units are examined. The utilization of a GA over a brute-force approach resulted in speedups up to 1.8 × 10 12 . New types of units, not frequently seen in OSCs, are suggested, and in total 5426 NFAs are discovered with the GA. Of these, 1087 NFAs are predicted to have a PCE greater than 18%, which is roughly the current record efficiency. While the symmetry of the sequence showed no correlation with PCE, analysis of the sequence arrangement revealed that higher performance can be achieved with a donor core and acceptor end groups. Future NFA designs should consider this strategy as an alternative to the current A-D-A'-D-A architecture.

14 SOLAR ENERGY↗
DOE OSTI2024

Unraveling the Formation Mechanisms of Highly Oriented Tin Perovskite with a 3D-over-2D Heterostructure

Tin-based perovskites (TinPVKs) have become the most promising candidates for lead-free perovskite solar cells, owing to its low toxicity and improved photovoltaic performance. However, due to the absence of 4f shell, TinPVKs suffer from uncontrolled crystallization, limiting the power conversion efficiency (PCE) of tin perovskite solar cells (TinPSCs). Here, we systematically study the ligand regulated crystallization process of TinPVK. We find that with elongated spin time, TinPVK crystals undergo reorientation and lateral growth. 3D α-phase FASnI3 and 2D (n = 2) and 2D (n = 1) phases emerge sequentially to form a “3D-over-2D” heterostructure via a proposed “diffusion-propagation” mechanism. TinPSCs exhibit improved open circuit voltage (V OC ) due to favorable energy level alignment of the 3D-over-2D heterostructure, with a champion PCE value of 13.07% and T 80 value of over 1200 h. Furthermore, this work provides mechanistic insights on controlled crystallization and heterostructure formation of TinPVKs, paving the way toward high-efficiency TinPSCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

LA17-V-InverseRadTransportProblem-PD2Kb. Final Project Report

In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Quantitative relationships between film morphology, charge carrier dynamics, and photovoltaic performance in bulk-heterojunction binary vs. ternary acceptor blends

Addressing pertinent and perplexing questions regarding why nonfullerene acceptors (NFAs) promote higher power conversion efficiencies (PCEs) than traditional fullerenes and how photoactive bulk heterojunction (BHJ) film morphology, charge photogeneration, and recombination dynamics dictate solar cell performance have stimulated many studies of polymer solar cells (PSCs), yet quantitative relationships remain limited. Better understanding in these areas offers the potential to advance materials design and device engineering, afford higher PCEs, and ultimate commercialization. Here we probe quantitative relationships between BHJ film morphology, charge carrier dynamics, and photovoltaic performance in model binary and ternary blend systems having a wide bandgap donor polymer, a fullerene, and a promising NFA. We show that optimal PC 71 BM incorporation in a PBDB-TF:ITIC-Th binary system matrix retains the original π-face-on orientation, ITIC-Th crystallinity and BHJ film crystallite dimensions, and reduces film upper surface ITIC-Th segregation. Such morphology changes together simultaneously increase hole (μ h ) and electron (μ e ) mobilities, facilitate light-activated ITIC-Th to PC 71 BM domain electron delocalization, reduce free charge carrier (FC) bimolecular recombination (BR) within PBDB-TF:ITIC-Th mixed regions, and increase FC extraction pathways viaPBDB-TF:PC 71 BM pairs. The interplay of these effects yields significantly enhanced inverted cell short-circuit current density (J SC ), fill factor (FF), and PCE. Unexpectedly, we also find that excessive PC 71 BM in the PBDB-TF:ITIC-Th binary system alters the PBDB-TF orientation to π-edge-on, increases large scale PC 71 BM-rich aggregations and BHJ upper surface PC 71 BM composition. Further, these morphology changes increase parasitic decay processes such as intersystem crossing from photoexcited PC 71 BM, compromising the J SC , FF, and PCE metrics. ITIC-Th X-ray diffraction reveals a unique sidechain-dominated molecular network with previously unknown sidechain-end group stacking, rationalizing the STEM and GIWAXS results, photophysics, and the high μ e . DFT computation reveals charge transfer networks within ITIC-Th crystallites, supporting excited-state electron delocalization from ITIC-Th to PC 71 BM. This structure–property understanding leads to a newly reported NFA blend with PCE near 17%.

14 SOLAR ENERGY↗
DOE OSTI2023

Integrated Large-Scale Data Management Platform for Photovoltaic Power Conversion Equipment (PCE) Reliability Data

To meet the demand for accuracy and real-time capability of PV system degradation evaluation, massive volume data is needed to run high-fidelity and high-efficiency simulations and perform advanced data analysis. However, PV farm operators have a series of difficulties with PV inverter data, such as data collection from multiple channels, massive data storage, data management and massive data analysis. To address these challenges, we developed an integrated data management platform capable of data acquisition, processing, storage, query, and performing big data analysis utilizing AI algorithms. The platform can also achieve data correctness verification and provide an effective distributed data management solution to retrieve massive data and establish a connection to distributed computational frameworks.

data management platform↗
DOE OSTI2023

Integrated Large-Scale Data Management Platform for Photovoltaic Power Conversion Equipment (PCE) Reliability Data: Preprint

To meet the demand for accuracy and real-time capability of PV system degradation evaluation, massive volume data is needed to run high-fidelity and high-efficiency simulations and perform advanced data analysis. However, PV farm operators have a series of difficulties with PV inverter data, such as data collection from multiple channels, massive data storage, data management and massive data analysis. To address these challenges, we developed an integrated data management platform capable of data acquisition, processing, storage, query, and performing big data analysis utilizing AI algorithms. The platform can also achieve data correctness verification and provide an effective distributed data management solution to retrieve massive data and establish a connection to distributed computational frameworks.

data management↗
DOE OSTI2022

Electrical edge effect induced photocurrent overestimation in low-light organic photovoltaics

In many literatures, the short-circuit current (J SC ) of indoor organic photovoltaics is overestimated, leading to severely wrong device performance evaluation and analysis. In this work, based on the equivalent circuit model, we demonstrate that electrical edge effect is sensitive to both transverse surface resistance and light intensity. At low light intensity, the electrical edge effect could lead to J SC being significantly overestimated, i.e., by 100% and even more. We show that for a PM6:Y6 device capped with a MoOX layer, when measured under 0.01 sun, the usually overlooked interface doping mechanism would lead to J SC and PCE overestimation by 51% and 15%, respectively. Besides, we show that the magnitude of J SC overestimation drastically increases with high photoactive-layer surface roughness. This work emphasized the significant electrical edge effect on J SC evaluations for low-light solar cells and is conducive to understanding the intrinsic mechanism of edge effect, promoting a healthier development of organic photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2024

Eliminating the Burn‐in Loss of Efficiency in Organic Solar Cells by Applying Dimer Acceptors as Supramolecular Stabilizers

Abstract The meta‐stable active layer morphology of organic solar cells (OSCs) is identified as the main cause of the rapid burn‐in loss of power conversion efficiency (PCE) during long‐term device operation. However, effective strategies to eliminate the associated loss mechanisms from the initial stage of device operation are still lacking, especially for high‐efficiency material systems. Herein, the introduction of molecularly engineered dimer acceptors with adjustable thermal transition properties into the active layer of OSCs to serve as supramolecular stabilizers for regulating the thermal transitions and optimizing the crystallization of the absorber composites is reported. By establishing intimate π‐π interactions with small‐molecule acceptors, these stabilizers can effectively reduce the trap‐state density (N t ) in the devices to achieve excellent PCEs over 19%. More importantly, the lowN t associated with an initially optimized morphology can be maintained under external stresses to significantly reduce the PCE burn‐in loss in devices. This research reveals a judicious approach to improving OPV stability by establishing a comprehensive correlation between material properties, active‐layer morphology, and device performance, for developing burn‐in‐free OSCs.

Chemistry↗
DOE OSTI2023

Enhancing Photostability of Sn-Pb Perovskite Solar Cells by an Alkylammonium Pseudo-Halogen Additive

High-performance tin-lead perovskite solar cells (PSCs) are needed for all-perovskite-tandem solar cells. However, iodide related fast photodegradation severely limits the operational stability of Sn-Pb perovskites despite the demonstrated high efficiency and thermal stability. Herein, this work employs an alkylammonium pseudo-halogen additive to enhance the power conversion efficiency (PCE) and photostability of methylammonium (MA)-free, Sn-Pb PSCs. Density functional theory (DFT) calculations reveal that the pseudo-halogen tetrafluoroborate (BF 4 - ) has strong binding capacity with metal ions (Sn 2+ /Pb 2+ ) in the Sn-Pb perovskite lattice, which lowers iodine vacancy formation. Upon combining BF 4 - with an octylammonium (OA + ) cation, the PCE of the device with a built-in light-scattering layer is boosted to 23.7%, which represents a new record for Sn-Pb PSCs. The improved efficiency benefits from the suppressed defect density. Under continuous 1 sun illumination, the OABF 4 embodied PSCs show slower generation of interstitial iodides and iodine, which greatly improves the device photostability under open-circuit condition. Moreover, the device based on OABF 4 retains 88% of the initial PCE for 1000 h under the maximum-power-point tracking (MPPT) without cooling.

14 SOLAR ENERGY↗
DOE OSTI2024

Identifying and Amplifying the Spontaneously Formed Photo‐Charge Contribution in Opaque and Semitransparent Organic Photovoltaics

Abstract Spontaneous photo‐charge (SP) generation within the non‐fullerene (NFA) bulk helps avoid exciton (EX) related loss as compared to the traditional heterojunction route in organic solar cells (OSCs). Unfortunately, the promising SP utilization attracts little attention at this time due to the lack of knowledge on its specific contribution to the photovoltaic performance and rational optimization in high‐efficiency devices. To fill the gap, the NFAs’ SP characteristics are related with their photocurrent loss and power conversion efficiency (PCE) in state‐of‐the‐art materials. Though higher SP population is good for efficient EX utilization, it simultaneously acts as an additional photo‐charge recombination channel. The former can be further enhanced by increasing the NFAs’ crystallinity with preferred lamellar growth, and the latter can be suppressed via electric doping. With the aid of the two‐step optimization strategy, the total photocurrent loss is reduced from 14.4% to 4.8%, accompanying with PCE increment from 16.9% to 18.5%. The SP utilization strategy is finally applied in the semitransparent OSCs (ST‐OSCs), due to its less heterojunction area sensitive photo‐charge generation characteristic. A light utilization efficiency (LUE) is then increased from 3.21% to 3.77%. The findings highlight the pursue of efficient SP utilization as a new design philosophy in future OSCs’ progresses.

Chemistry↗
DOE OSTI2022

Reduction of Chlorinated Ethenes by Ag- and Cu-Amended Green Rust

Chlorinated ethenes have been used extensively as solvents, degreasers, and dry-cleaning agents in a range of commercial and industrial applications. This has created a legacy of contaminated soils and groundwater, particularly with respect to perchloroethylene (PCE; a.k.a. tetrachloroethene—C 2 Cl 4 ), and trichloroethylene (TCE; a.k.a. trichloroethene—C 2 HCl 3 ), prompting the development of a wide array of treatment technologies for remediation of chlorinated ethene-contaminated environments. Green rusts are highly redox-active layered Fe(II)-Fe(III) hydroxides that have been shown to be facile reductants for a wide range of organic and inorganic pollutants. The reduction of chlorinated ethenes [vinyl chloride (VC); 1,1-dichloroethene(11DCE), cis-1,2-dichloroethene (c12DCE), trans-1,2-dichloroethene (t12DCE), TCE, and PCE] was examined in aqueous suspensions of green rust, alone as well as with the addition of Ag(I) (AgGR) or Cu(II) (CuGR). Green rust alone was ineffective as a reductant for the reductive dechlorination for all of the chlorinated ethenes. Near-complete removal of PCE was observed in the presence of AgGR, but all other chlorinated ethenes were essentially non-reactive. Partial removal of chlorinated ethenes was observed in the presence of CuGR, particularly 11DCE (34%), t12DCE (51%), and VC (66%). Significant differences were observed in the product distributions of chlorinated ethene reduction by AgGR and CuGR. The effectiveness of Ag(I)- and Cu(II)-amended green rusts for removal of chlorinated ethenes may be improved under different conditions (e.g., pH and interlayer anion) and warrants further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

Constructing surrogate models for uncertainty quantification (UQ) on complex partial differential equations (PDEs) having inherently high-dimensional O(10 n ), n ≥ 2, stochastic inputs (e.g., forcing terms, boundary conditions, initial conditions) poses tremendous challenges. The “curse of dimensionality” can be addressed with suitable unsupervised learning techniques used as a pre-processing tool to encode inputs onto lower-dimensional subspaces while retaining its structural information and meaningful properties. In this work, we review and investigate thirteen dimension reduction methods including linear and nonlinear, spectral, blind source separation, convex and non-convex methods and utilize the resulting embeddings to construct a mapping to quantities of interest via polynomial chaos expansions (PCE). Here, we refer to the general proposed approach as manifold PCE (m-PCE), where manifold corresponds to the latent space resulting from any of the studied dimension reduction methods. To investigate the capabilities and limitations of these methods we conduct numerical tests for three physics-based systems (treated as black-boxes) having high-dimensional stochastic inputs of varying complexity modeled as both Gaussian and non-Gaussian random fields to investigate the effect of the intrinsic dimensionality of input data. We demonstrate both the advantages and limitations of the unsupervised learning methods and we conclude that a suitable m-PCE model provides a cost-effective approach compared to alternative algorithms proposed in the literature, including recently proposed expensive deep neural network-based surrogates and can be readily applied for high-dimensional UQ in stochastic PDEs.

42 ENGINEERING↗